Full_Nutrient_Models
Hannah Merges
2024-06-17
Loading libraries
Loading Data
pHSlope <- read_csv(here("Data", "pHSlope.csv")) ## manually deleted BLANK DATA on MAY 30th
calc.data <- read_csv(here("Data", "Titrations", "Calc_TArates.csv"))
full_calc_data <- read_csv(here("Data", "full_calc_data.csv"))
#RespoR_Normalized_Full_ExcelUpdates <- read_csv(here::here("Data","RespoFiles", "Respo_RNormalized_AllRates.csv"))
#NEC_wnuts <- read_csv(here("Data", "NECnuts_withpH.csv"))
#FULL_RespoNEC_allParams <- read_csv(here("Data", "RespoR_Normalized_Full_withNEC_ExcelUpdates.csv"))
RespoR_Normalized_Full_withNEC_nutrients <- read_csv(here::here("Data", "RespoR_Normalized_Full_withNEC_andallnutrients.csv"))Tidy the dataframes and play around with them to explore data
calculated mean, sd and var — maybe this is something to come back to only if stick with SGD dils as final x axis
## calculate mean, variances, and sd of O2 rates so we have that work with just in case
#RespoR_Normalized_Full_meanvar <- RespoR_Normalized_Full_ExcelUpdates %>%
# group_by(SGD_number, site, P_R) %>%
# summarize(mean_umol = mean(umol.cm2.hr, na.rm=TRUE),
# var_umol = var(umol.cm2.hr, na.rm=TRUE),
# sd_umol = sd(umol.cm2.hr, na.rm = TRUE)) %>%
# filter(!is.infinite(mean_umol))
#RespoR_Normalized_Full2 <- RespoR_Normalized_Full_ExcelUpdates %>%
#left_join(RespoR_Normalized_Full_meanvar, join_by(SGD_number, site, P_R))
## for calc data as well
#full.calc.data_meanvar <- full_calc_data %>%
# filter(!is.infinite(umol.cm2.hr)) %>%
# group_by(SGD_number, site) %>%
# summarize(mean_umol = mean(umol.cm2.hr, na.rm=TRUE),
# var_umol = var(umol.cm2.hr, na.rm=TRUE),
# sd_umol = sd(umol.cm2.hr, na.rm = TRUE))
### and with the NEC_nuts df
#full.calc.data_meanvar_withnuts <- NEC_wnuts %>%
# filter(!is.infinite(umol.cm2.hr)) %>%
# group_by(SGD_number, site) %>% ## this groups all the 8 replicates together for one average
# summarize(mean_umol = mean(umol.cm2.hr, na.rm=TRUE),
# var_umol = var(umol.cm2.hr, na.rm=TRUE),
# sd_umol = sd(umol.cm2.hr, na.rm = TRUE))THINGS TO CONSIDER:
Note: pH is also calculated based on measurements taken WHEN (before or after 12 hours??)
PLOT CENTRAL: series of plots for each physio measurement (R, GP, NP, NEC) per each env param (sal, pH, NN, phos, silicate, ammonia, and TA)
Goal: create models to see if specific nutrients have an effect on the O2 rates
starting with VARARI, RESPIRATION - updated on June 13th
RespoR_Normalized_Full_AllInfo <- RespoR_Normalized_Full_withNEC_nutrients %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date),
NN_umolL=as.numeric(NN_umolL),
ammonia_umolL=as.numeric(ammonia_umolL),
silicate_umolL=as.numeric(silicate_umolL),
phosphate_umolL=as.numeric(phosphate_umolL),
new_pH=as.numeric(new_pH),
salinity=as.numeric(salinity),
TA_initial=as.numeric(TA_initial),
umol.cm2.hr=as.numeric(umol.cm2.hr))
Nutrient_Models_Varari_R <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
drop_na(NN_umolL) %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr))
Nutrient_Models_Varari_R<-Nutrient_Models_Varari_R[-c(47),] ## removes the outlier (really low value) -- CHECK THIS - good as of June 1st
#######################
## NN ##
########################
NNbyRplot <- Nutrient_Models_Varari_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date),
NN_umolL=as.numeric(NN_umolL)) %>%
# filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=NN_umolL,
y=umol.cm2.hr)) +
coord_trans(x="log") +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "N+N (umolL)",
y = "Rate (umol O2 cm2 hr-1)",
title = "N+N for Varari") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NNbyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "Respiration", "NN_plot.jpg"),
width = 10, height = 7)
## normal model with full nesting and random effects
Varari_NN_resp <- lmer(data = Nutrient_Models_Varari_R,
umol.cm2.hr ~ poly(NN_umolL, degree=2) + (1|new_colonynumber))
anova(Varari_NN_resp) ## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(NN_umolL, degree = 2) 0.0011948 0.0005974 2 60.974 0.2068 0.8138summary(Varari_NN_resp)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: umol.cm2.hr ~ poly(NN_umolL, degree = 2) + (1 | new_colonynumber)
## Data: Nutrient_Models_Varari_R
##
## REML criterion at convergence: -175.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.98926 -0.61735 0.06235 0.69000 1.98122
##
## Random effects:
## Groups Name Variance Std.Dev.
## new_colonynumber (Intercept) 0.003359 0.05796
## Residual 0.002889 0.05375
## Number of obs: 68, groups: new_colonynumber, 8
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 0.297391 0.021507 6.171350 13.827 7.09e-06 ***
## poly(NN_umolL, degree = 2)1 -0.047879 0.074475 64.936337 -0.643 0.523
## poly(NN_umolL, degree = 2)2 0.008506 0.056700 59.664886 0.150 0.881
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) p(NN_L,d=2)1
## p(NN_L,d=2)1 0.007
## p(NN_L,d=2)2 -0.004 -0.209#######################
## NH4 ##
########################
NH4byRplot <- Nutrient_Models_Varari_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date),
ammonia_umolL=as.numeric(ammonia_umolL)) %>%
# filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=ammonia_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
labs(x = "Logged NH4 (umolL)",
y = "Rate (umol O2 cm2 hr-1)",
title = "NH4 for Varari") +
# facet_wrap(~date, scales = "free_x") +
theme(axis.text.x=element_text(size=6),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NH4byRplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "Respiration", "NH4_plot.jpg"),
width = 10, height = 7)
### model
Varari_NH4_resp <- lmer(data = Nutrient_Models_Varari_R,
umol.cm2.hr ~ poly(ammonia_umolL, degree=2) + (1|new_colonynumber))
anova(Varari_NH4_resp) ## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(ammonia_umolL, degree = 2) 0.007153 0.0035765 2 60.535 1.2808 0.2852summary(Varari_NH4_resp)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: umol.cm2.hr ~ poly(ammonia_umolL, degree = 2) + (1 | new_colonynumber)
## Data: Nutrient_Models_Varari_R
##
## REML criterion at convergence: -177.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0008 -0.5524 0.2005 0.6641 1.7752
##
## Random effects:
## Groups Name Variance Std.Dev.
## new_colonynumber (Intercept) 0.003314 0.05757
## Residual 0.002792 0.05284
## Number of obs: 68, groups: new_colonynumber, 8
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 0.29765 0.02134 6.81028 13.947 2.93e-06
## poly(ammonia_umolL, degree = 2)1 -0.04513 0.05573 59.31215 -0.810 0.421
## poly(ammonia_umolL, degree = 2)2 -0.08202 0.06230 62.07656 -1.317 0.193
##
## (Intercept) ***
## poly(ammonia_umolL, degree = 2)1
## poly(ammonia_umolL, degree = 2)2
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) p(_L,d=2)1
## pl(_L,d=2)1 -0.003
## pl(_L,d=2)2 -0.003 -0.074#######################
## PO4 ##
########################
PhosbyRplot <- Nutrient_Models_Varari_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
# filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#facet_wrap(~date, scales = "free_x") +
labs(x = "Logged Phosphate (umolL)",
y = "Rate (umol O2 cm2 hr-1)",
title = "Phosphate for Varari") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
PhosbyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "Respiration", "PO4_plot.jpg"),
width = 10, height = 7)
Varari_PO4_resp <- lmer(data = Nutrient_Models_Varari_R,
umol.cm2.hr ~ poly(phosphate_umolL, degree=2) + (1|date/new_colonynumber))
anova(Varari_PO4_resp) ## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value
## poly(phosphate_umolL, degree = 2) 0.0059282 0.0029641 2 58.848 1.0416
## Pr(>F)
## poly(phosphate_umolL, degree = 2) 0.3593summary(Varari_PO4_resp)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula:
## umol.cm2.hr ~ poly(phosphate_umolL, degree = 2) + (1 | date/new_colonynumber)
## Data: Nutrient_Models_Varari_R
##
## REML criterion at convergence: -179.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.9781 -0.5558 0.1050 0.7125 1.7957
##
## Random effects:
## Groups Name Variance Std.Dev.
## new_colonynumber:date (Intercept) 0.0004542 0.02131
## date (Intercept) 0.0043061 0.06562
## Residual 0.0028458 0.05335
## Number of obs: 68, groups: new_colonynumber:date, 8; date, 4
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 0.30789 0.03452 2.69540 8.918
## poly(phosphate_umolL, degree = 2)1 -0.07038 0.05511 58.51644 -1.277
## poly(phosphate_umolL, degree = 2)2 0.03437 0.05796 59.30827 0.593
## Pr(>|t|)
## (Intercept) 0.00447 **
## poly(phosphate_umolL, degree = 2)1 0.20660
## poly(phosphate_umolL, degree = 2)2 0.55545
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) p(_L,d=2)1
## pl(_L,d=2)1 -0.020
## pl(_L,d=2)2 -0.020 0.061#######################
## SiO3 ##
########################
SilicatebyRplot <- Nutrient_Models_Varari_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
# filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=silicate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged Silicate (umolL)",
y = "Rate (umol O2 cm2 hr-1)",
title = "Respiration Rates for Varari with Silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SilicatebyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "Respiration", "SiO4_plot.jpg"),
width = 10, height = 7)
Varari_SiO4_resp <- lmer(data = Nutrient_Models_Varari_R,
umol.cm2.hr ~ poly(silicate_umolL, degree=2) + (1|date/new_colonynumber))
anova(Varari_SiO4_resp) ## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value
## poly(silicate_umolL, degree = 2) 0.0038834 0.0019417 2 58.375 0.6757
## Pr(>F)
## poly(silicate_umolL, degree = 2) 0.5127summary(Varari_SiO4_resp)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula:
## umol.cm2.hr ~ poly(silicate_umolL, degree = 2) + (1 | date/new_colonynumber)
## Data: Nutrient_Models_Varari_R
##
## REML criterion at convergence: -178.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.92660 -0.58448 0.07048 0.65088 2.08115
##
## Random effects:
## Groups Name Variance Std.Dev.
## new_colonynumber:date (Intercept) 0.0004591 0.02143
## date (Intercept) 0.0044897 0.06701
## Residual 0.0028735 0.05361
## Number of obs: 68, groups: new_colonynumber:date, 8; date, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 0.30716 0.03519 2.75548 8.729 0.00437
## poly(silicate_umolL, degree = 2)1 -0.05105 0.05469 58.20866 -0.933 0.35447
## poly(silicate_umolL, degree = 2)2 0.04244 0.05666 58.58146 0.749 0.45685
##
## (Intercept) **
## poly(silicate_umolL, degree = 2)1
## poly(silicate_umolL, degree = 2)2
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) p(_L,d=2)1
## pl(_L,d=2)1 0.007
## pl(_L,d=2)2 -0.005 -0.061#######################
## pH ##
########################
pHbyRplot <- Nutrient_Models_Varari_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=new_pH,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged pH",
y = "Rate (umol O2 cm2 hr-1)",
title = "Respiration Rates for Varari with pH") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
pHbyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "Respiration", "pH_plot.jpg"),
width = 10, height = 7)
Varari_pH_resp <- lmer(data = Nutrient_Models_Varari_R,
umol.cm2.hr ~ poly(new_pH, degree=2) + (1|date/new_colonynumber))
anova(Varari_pH_resp) ## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(new_pH, degree = 2) 0.011157 0.0055784 2 60.127 1.9939 0.1451summary(Varari_pH_resp)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: umol.cm2.hr ~ poly(new_pH, degree = 2) + (1 | date/new_colonynumber)
## Data: Nutrient_Models_Varari_R
##
## REML criterion at convergence: -181.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.4914 -0.5442 0.1513 0.7130 1.8833
##
## Random effects:
## Groups Name Variance Std.Dev.
## new_colonynumber:date (Intercept) 0.000527 0.02296
## date (Intercept) 0.002873 0.05360
## Residual 0.002798 0.05289
## Number of obs: 68, groups: new_colonynumber:date, 8; date, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 0.30650 0.02901 2.46858 10.566 0.00408 **
## poly(new_pH, degree = 2)1 -0.12627 0.06460 60.90472 -1.955 0.05522 .
## poly(new_pH, degree = 2)2 -0.02731 0.05572 59.35504 -0.490 0.62584
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) p(_H,d=2)1
## pl(_H,d=2)1 0.004
## pl(_H,d=2)2 -0.017 0.042#######################
## salinity ##
########################
salinitybyRplot <- Nutrient_Models_Varari_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged salinity",
y = "Rate (umol O2 cm2 hr-1)",
title = "Respiration Rates for Varari with salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
salinitybyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "Respiration", "salinity_plot.jpg"),
width = 10, height = 7)
Varari_sal_resp <- lmer(data = Nutrient_Models_Varari_R,
umol.cm2.hr ~ poly(salinity, degree=2) + (1|date/new_colonynumber))
anova(Varari_sal_resp) ## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(salinity, degree = 2) 0.0033903 0.0016952 2 59.418 0.5861 0.5597summary(Varari_sal_resp)## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: umol.cm2.hr ~ poly(salinity, degree = 2) + (1 | date/new_colonynumber)
## Data: Nutrient_Models_Varari_R
##
## REML criterion at convergence: -179.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0044 -0.6109 0.1176 0.6576 1.9256
##
## Random effects:
## Groups Name Variance Std.Dev.
## new_colonynumber:date (Intercept) 0.0004604 0.02146
## date (Intercept) 0.0041284 0.06425
## Residual 0.0028921 0.05378
## Number of obs: 68, groups: new_colonynumber:date, 8; date, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 0.308906 0.033949 2.738426 9.099 0.004 **
## poly(salinity, degree = 2)1 0.078075 0.080012 60.685108 0.976 0.333
## poly(salinity, degree = 2)2 -0.005349 0.062069 59.906010 -0.086 0.932
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) p(,d=2)1
## ply(s,d=2)1 0.057
## ply(s,d=2)2 0.041 0.360#######################
## TA ##
########################
TAbyRplot <- Nutrient_Models_Varari_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
# filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#facet_wrap(~date, scales = "free_x") +
labs(x = "Logged TA (umolL)",
y = "Rate (umol O2 cm2 hr-1)",
title = "TA for Varari") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "Respiration", "TA_plot.jpg"),
width = 10, height = 7)Varari NP plots with nutrients
### make new dataset
Nutrient_Models_Varari_NP <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
drop_na(NN_umolL) %>%
filter(P_R=="NP") %>%
filter(!is.infinite(umol.cm2.hr))
## pH
pHbyNPplot <- Nutrient_Models_Varari_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date)) %>%
#SGD_number=as.factor(SGD_number)) %>%
ggplot(aes(x=new_pH,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "pH",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Varari with pH") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
pHbyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "NetPhotosynthesis", "pH_plot.jpg"),
width = 10, height = 7)
## salinity
salinitybyNPplot <- Nutrient_Models_Varari_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "salinity",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Varari with salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
salinitybyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "NetPhotosynthesis", "sal_plot.jpg"),
width = 10, height = 7)
## phosphate
phosphatebyNPplot <- Nutrient_Models_Varari_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date),
SGD_number=as.factor(SGD_number)) %>%
filter(phosphate_umolL<1) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Phosphate",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Varari with Phosphate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
phosphatebyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "NetPhotosynthesis", "phosphate_plot.jpg"),
width = 10, height = 7)
## nitrates
NNbyNPplot <- Nutrient_Models_Varari_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=NN_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "NN",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Varari with NN") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NNbyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "NetPhotosynthesis", "NN_plot.jpg"),
width = 10, height = 7)
## silicate
silicatebyNPplot <- Nutrient_Models_Varari_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=silicate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Silicate",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Varari with silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
silicatebyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "NetPhotosynthesis", "silicate_plot.jpg"),
width = 10, height = 7)
## ammonia
ammoniabyNPplot <- Nutrient_Models_Varari_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=ammonia_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Ammonia",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Varari with Ammonia") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
ammoniabyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "NetPhotosynthesis", "ammonia_plot.jpg"),
width = 10, height = 7)
## TA
TAbyNPplot <- Nutrient_Models_Varari_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Varari with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "NetPhotosynthesis", "TA_plot.jpg"),
width = 10, height = 7)Varari GP for each nutrient
Nutrient_Models_Varari_GP <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
drop_na(NN_umolL) %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr))
## pH
pHbyGPplot <- Nutrient_Models_Varari_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=new_pH,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "pH",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with pH") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
pHbyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "GrossPhotosynthesis", "pH_plot.jpg"),
width = 10, height = 7)
## TA
TAbyGPplot <- Nutrient_Models_Varari_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "GrossPhotosynthesis", "TA_plot.jpg"),
width = 10, height = 7)
## salinity
salinitybyGPplot <- Nutrient_Models_Varari_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "salinity",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
salinitybyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "GrossPhotosynthesis", "salinity_plot.jpg"),
width = 10, height = 7)
## ammonia
ammoniabyGPplot <- Nutrient_Models_Varari_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=ammonia_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "ammonia",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with ammonia") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
ammoniabyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "GrossPhotosynthesis", "ammonia_plot.jpg"),
width = 10, height = 7)
## silicate
silicatebyGPplot <- Nutrient_Models_Varari_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=silicate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
geom_smooth(method = "lm", formula="y~poly(x,2)") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "silicate",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
silicatebyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "GrossPhotosynthesis", "silicate_plot.jpg"),
width = 10, height = 7)
## NN
NNbyGPplot <- Nutrient_Models_Varari_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=NN_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "NN",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with NN") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NNbyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "GrossPhotosynthesis", "NN_plot.jpg"),
width = 10, height = 7)
## phosphate
phosphatebyGPplot <- Nutrient_Models_Varari_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "phosphate",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with phosphate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
phosphatebyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "GrossPhotosynthesis", "phosphate_plot.jpg"),
width = 10, height = 7)
Varari_PO4_GP <- lmer(data = Nutrient_Models_Varari_GP,
umol.cm2.hr ~ poly(phosphate_umolL, degree=2) + (1|date/new_colonynumber))
anova(Varari_PO4_resp) ## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value
## poly(phosphate_umolL, degree = 2) 0.0059282 0.0029641 2 58.848 1.0416
## Pr(>F)
## poly(phosphate_umolL, degree = 2) 0.3593Varari Calcification just with SGD dils
SGDdilsbyVplot <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="C") %>%
#filter(sample_ID_edit!="Varari_Col4_Dil9_Light_Day2") %>% ### NOT SURE WHY THIS IS HERE/CAUSING AN ERROR (tried to knit)
filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=SGD_number,
y=umol.cm2.hr)) +
geom_point(size=4) +
theme_bw() +
coord_trans(x="log") +
geom_smooth(method = "lm", se=TRUE, color="black") +
geom_hline(yintercept = 0) +
# facet_wrap(~date, scales = "free_x") +
labs(x = "SGD Dils",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyVplot 
SGDdilsbyVplot2 <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=4, aes(color=new_colonynumber)) +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
coord_trans(x ="log") +
theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method = "lm", color="black") +
geom_hline(yintercept = 0) +
labs(x = "log SGD Dils",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyVplot2
model_ex <- lmer(umol.cm2.hr ~ log(SGD_number+1) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(SGD_number + 1) 0.11101 0.11101 1 60.079 7.3097 0.008907 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Varari Calcification for each nutrient
Nutrient_Models_Varari_NEC <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
drop_na(NN_umolL) %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr))
## ammonia
ammoniabyVplot <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=ammonia_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~date, scales = "free_x") +
labs(x = "ammonia",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with Ammonia") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
ammoniabyVplot
ggsave(here::here("Outputs", "NutrientAnalyses", "Varari", "Calcification", "NECbyAmmonia.jpg"))
### silicate
silicatebyVplot <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=silicate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~date, scales = "free_x") +
labs(x = "silicate",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with Silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
silicatebyVplot
ggsave(here::here("Outputs", "NutrientAnalyses", "Varari", "Calcification", "NECbySilicate.jpg"))
modelsilicate_NEC_V <- lmer(umol.cm2.hr ~ poly(silicate_umolL, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Varari_NEC)
anova(modelsilicate_NEC_V)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(silicate_umolL, degree = 2) 0.11222 0.05611 2 60.604 3.63 0.03243 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1### NN
NNbyVplot <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=NN_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~date, scales = "free_x") +
labs(x = "NN",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with NN") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NNbyVplot
ggsave(here::here("Outputs", "NutrientAnalyses", "Varari", "Calcification", "NECbyNN.jpg"))
### Phos
PhosbyVplot <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
filter(phosphate_umolL<0.7) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method="lm", formula="y~poly(x,2)") +
coord_trans(x="log") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "Phosphate",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with Phosphate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
PhosbyVplot
ggsave(here::here("Outputs", "NutrientAnalyses", "Varari", "Calcification", "NECbyPhosphate.jpg"))
##############
## quick model
###############
modelPhos_NEC_V <- lmer(umol.cm2.hr ~ poly(phosphate_umolL, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Varari_NEC)
anova(modelPhos_NEC_V)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value
## poly(phosphate_umolL, degree = 2) 0.24722 0.12361 2 61.029 9.3418
## Pr(>F)
## poly(phosphate_umolL, degree = 2) 0.0002888 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1### pH
pHbyVplot <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=new_pH,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
#facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "pH",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with pH") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
pHbyVplot
ggsave(here::here("Outputs", "NutrientAnalyses", "Varari", "Calcification", "NECbypH.jpg"))
### salinity
SalinitybyVplot <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
filter(phosphate_umolL<1) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "Salinity",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with Salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SalinitybyVplot
ggsave(here::here("Outputs", "NutrientAnalyses", "Varari", "Calcification", "NECbySalinity.jpg"))
modelsalinity_NEC_V <- lmer(umol.cm2.hr ~ poly(salinity, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Varari_NEC)
anova(modelsalinity_NEC_V)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(salinity, degree = 2) 0.08607 0.043035 2 60.58 2.7863 0.06957 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1### TA
TAbyVplot <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(aes(color=new_colonynumber), size=3) +
theme_bw() +
geom_smooth(method="lm") +
coord_trans(x="log") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
#facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbyVplot
ggsave(here::here("Outputs", "NutrientAnalyses", "Varari", "Calcification", "NECbyTA.jpg"))
modelTA_NEC_V <- lmer(umol.cm2.hr ~ poly(TA_initial, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Varari_NEC)
anova(modelTA_NEC_V)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(TA_initial, degree = 2) 0.165 0.082499 2 62.029 5.6917 0.005377 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1quick visualization of TA at both sites
TA is significant (0.002)
### plot both sites together for NEC Phos
TA_bothsites <- RespoR_Normalized_Full_AllInfo %>%
drop_na(umol.cm2.hr) %>%
filter(phosphate_umolL<1) %>%
filter(P_R=="C") %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date),
SGD_number=as.factor(SGD_number)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr,
color=new_colonynumber)) +
geom_point(size=3) +
theme_bw() +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Both Sites with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TA_bothsites
linearmod_bothsites_TA <- lmer(umol.cm2.hr ~ TA_initial + (1|new_colonynumber),
data=RespoR_Normalized_Full_AllInfo %>%
filter(umol.cm2.hr!="Inf") %>%
filter(P_R=="C"))
anova(linearmod_bothsites_TA)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## TA_initial 0.10498 0.10498 1 115.09 8.8678 0.00354 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Cabral NP plots
Nutrient_Models_Cabral_NP <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
drop_na(NN_umolL) %>%
filter(P_R=="NP") %>%
filter(!is.infinite(umol.cm2.hr))
## pH
pHbyNPplot <- Nutrient_Models_Cabral_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=new_pH,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "pH",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Cabral with pH") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
pHbyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "NetPhotosynthesis", "pH_plot.jpg"),
width = 10, height = 7)
## salinity
salbyNPplot <- Nutrient_Models_Cabral_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "salinity",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Cabral with salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
salbyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "NetPhotosynthesis", "salinity_plot.jpg"),
width = 10, height = 7)
## phosphate
phosphatebyNPplot <- Nutrient_Models_Cabral_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr,
color=new_colonynumber)) +
geom_point(size=3) +
theme_bw() +
coord_trans(x="log") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "phosphate",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Cabral with phosphate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
phosphatebyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "NetPhotosynthesis", "phosphate_plot.jpg"),
width = 10, height = 7)
## ammonia
ammoniabyNPplot <- Nutrient_Models_Cabral_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=ammonia_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "ammonia",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Cabral with ammonia") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
ammoniabyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "NetPhotosynthesis", "ammonia_plot.jpg"),
width = 10, height = 7)
## NN
NNbyNPplot <- Nutrient_Models_Cabral_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=NN_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "NN",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Cabral with NN") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NNbyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "NetPhotosynthesis", "NN_plot.jpg"),
width = 10, height = 7)
## silicate
silicatebyNPplot <- Nutrient_Models_Cabral_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=silicate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "silicate",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Cabral with silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
silicatebyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "NetPhotosynthesis", "silicate_plot.jpg"),
width = 10, height = 7)
## TA
TAbyNPplot <- Nutrient_Models_Cabral_NP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Cabral with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbyNPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "NetPhotosynthesis", "TA_plot.jpg"),
width = 10, height = 7)Cabral R plots
Nutrient_Models_Cabral_R <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
drop_na(NN_umolL) %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr))
## pH
pHbyRplot <- Nutrient_Models_Cabral_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=new_pH,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "pH",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Cabral with pH") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
pHbyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Respiration", "pH_plot.jpg"),
width = 10, height = 7)
## TA
TAbyRplot <- Nutrient_Models_Cabral_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Cabral with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Respiration", "TA_plot.jpg"),
width = 10, height = 7)
## salinity
salinitybyRplot <- Nutrient_Models_Cabral_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "salinity",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Cabral with salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
salinitybyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Respiration", "salinity_plot.jpg"),
width = 10, height = 7)
## phosphate
phosphatebyRplot <- Nutrient_Models_Cabral_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "phosphate",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Cabral with phosphate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
phosphatebyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Respiration", "phosphate_plot.jpg"),
width = 10, height = 7)
## ammonia
ammoniabyRplot <- Nutrient_Models_Cabral_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=ammonia_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "ammonia",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Cabral with ammonia") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
ammoniabyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Respiration", "ammonia_plot.jpg"),
width = 10, height = 7)
## NN
NNbyRplot <- Nutrient_Models_Cabral_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=NN_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "NN",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Cabral with NN") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NNbyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Respiration", "NN_plot.jpg"),
width = 10, height = 7)
## silicate
silicatebyRplot <- Nutrient_Models_Cabral_R %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=silicate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "silicate",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Cabral with silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
silicatebyRplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Respiration", "silicate_plot.jpg"),
width = 10, height = 7)Cabral GP plots
Nutrient_Models_Cabral_GP <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
drop_na(NN_umolL) %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr))
## pH
pHbyGPplot <- Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=new_pH,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "pH",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with pH") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
pHbyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "GrossPhotosynthesis", "pH_plot.jpg"),
width = 10, height = 7)
### TA
TAbyGPplot <- Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "GrossPhotosynthesis", "TA_plot.jpg"),
width = 10, height = 7)
## salinity
salinitybyGPplot <- Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "salinity",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
salinitybyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "GrossPhotosynthesis", "salinity_plot.jpg"),
width = 10, height = 7)
## phosphate
phosphatebyGPplot <- Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "phosphate",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with phosphate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
phosphatebyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "GrossPhotosynthesis", "phosphate_plot.jpg"),
width = 10, height = 7)
## ammonia
ammoniabyGPplot <- Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=ammonia_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "ammonia",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with ammonia") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
ammoniabyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "GrossPhotosynthesis", "ammonia_plot.jpg"),
width = 10, height = 7)
## NN
NNbyGPplot <- Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=NN_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "NN",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with NN") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NNbyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "GrossPhotosynthesis", "NN_plot.jpg"),
width = 10, height = 7)
## silicate
silicatebyGPplot <- Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=silicate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "silicate",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
silicatebyGPplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "GrossPhotosynthesis", "silicate_plot.jpg"),
width = 10, height = 7)Cabral NEC plots
Nutrient_Models_Cabral_NEC <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
drop_na(NN_umolL) %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr))
## just by SGD dilutions first
SGDdilsbyCplot <- Nutrient_Models_Cabral_NEC %>%
filter(umol.cm2.hr<1) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
coord_trans(x="log") +
theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method = "lm", color="black") +
geom_hline(yintercept = 0) +
labs(x = "log SGD Dils",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyCplot
## ammonia
ammoniabyCplot <- Nutrient_Models_Cabral_NEC %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=ammonia_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "ammonia",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with ammonia") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
ammoniabyCplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Calcification", "NECbyAmmonia.jpg"),
width = 10, height = 7)
### silicate
silicatebyCplot <- Nutrient_Models_Cabral_NEC %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(silicate_umolL+1),
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Silicate",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with Silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
silicatebyCplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Calcification", "NECbySilicate.jpg"),
width = 10, height = 7)
modelsilicate_NEC_C <- lmer(umol.cm2.hr ~ poly(silicate_umolL, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Cabral_NEC)
anova(modelsilicate_NEC_C)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(silicate_umolL, degree = 2) 0.014263 0.0071314 2 45.339 0.9636 0.3892### NN
NNbyCplot <- Nutrient_Models_Cabral_NEC %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=NN_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "NN",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with NN") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NNbyCplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Calcification", "NECbyNN.jpg"),
width = 10, height = 7)
### Phos
PhosbyCplot <- Nutrient_Models_Cabral_NEC %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
geom_smooth(method="lm") +
theme_bw() +
#facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "Phosphate",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with Phosphate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
PhosbyCplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Calcification", "NECbyPhosphate.jpg"),
width = 10, height = 7)
###### salinity
salinitybyCplot <- Nutrient_Models_Cabral_NEC %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "salinity",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with Salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
salinitybyCplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Calcification", "NECbySalinity.jpg"),
width = 10, height = 7)
modelsalinity_NEC_C <- lmer(umol.cm2.hr ~ poly(salinity, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Cabral_NEC)
anova(modelsalinity_NEC_C)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(salinity, degree = 2) 0.019832 0.0099159 2 45.503 1.3664 0.2653###### pH
pHbyCplot <- Nutrient_Models_Cabral_NEC %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=new_pH,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
geom_smooth(method="lm", formula="y~poly(x,2)") +
#facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "Logged pH",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with pH") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
pHbyCplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Calcification", "NECbypH.jpg"),
width = 10, height = 7)
modelpH_NEC_C <- lmer(umol.cm2.hr ~ poly(new_pH, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Cabral_NEC)
anova(modelpH_NEC_C)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(new_pH, degree = 2) 0.043929 0.021964 2 47.29 3.3008 0.04551 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## TA
TAbyCplot <- Nutrient_Models_Cabral_NEC %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
geom_smooth(method="lm") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbyCplot
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "Calcification", "NECbyTA.jpg"),
width = 10, height = 7)
modelTA_NEC_C <- lmer(umol.cm2.hr ~ poly(TA_initial, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Cabral_NEC)
anova(modelTA_NEC_C)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(TA_initial, degree = 2) 0.012841 0.0064206 2 47.316 0.8827 0.4204#############################
## just the SGD dilution plots
#############################
SGDdilsbyCplot + SGDdilsbyVplot2
ggsave(here::here("Outputs", "NutrientAnalyses", "CabralandVarari_NEC_bySGDDils.jpg"),
width=12, height=7)Take the average of all replicates per SGD treatment to get one value per treatment and plot - May 31st
NEC_wnuts_averaged <- RespoR_Normalized_Full_AllInfo %>%
# filter(sample_ID_edit!="Varari_Col4_Dil9_Light_Day2") %>%
drop_na(umol.cm2.hr) %>%
filter(!is.infinite(umol.cm2.hr)) %>%
filter(umol.cm2.hr<1) %>%
group_by(site, SGD_number) %>%
summarize(avg_umol = mean(umol.cm2.hr))
### plot for Varari and Cabral
NECby_avgSGDdils_plot <- NEC_wnuts_averaged %>%
#filter(site=="Varari") %>%
ggplot(aes(x=log(SGD_number+1),
y=avg_umol,
color=as.factor(SGD_number))) +
geom_point(size=4) +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
# theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method="lm", formula="y~poly(x,2)", color="black") +
geom_hline(yintercept = 0) +
facet_wrap(~site) +
labs(x = "log SGD Dils",
y = "Rate (umol O2 cm2 hr-1)",
title = "NEC Rates for averaged SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NECby_avgSGDdils_plot
ggsave(here::here("Outputs", "NutrientAnalyses", "NEC_SGDavg_bothsites.jpg"))
#########################################
### run models on the averaged SGD dils bc Varari looks nonlinear
#########################################
NEC_wnuts_averaged_V <- NEC_wnuts_averaged %>%
filter(site=="Varari")
NEC_wnuts_averaged_C <- NEC_wnuts_averaged %>%
filter(site=="Cabral")
## varari
Varari_avgSGD_NEC <- lm(avg_umol ~ SGD_number, data = NEC_wnuts_averaged_V)
summary(Varari_avgSGD_NEC)##
## Call:
## lm(formula = avg_umol ~ SGD_number, data = NEC_wnuts_averaged_V)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.086090 0.000853 0.010773 0.013226 0.072247
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.382970 0.021044 18.20 3.74e-07 ***
## SGD_number -0.005205 0.013691 -0.38 0.715
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05248 on 7 degrees of freedom
## Multiple R-squared: 0.02023, Adjusted R-squared: -0.1197
## F-statistic: 0.1445 on 1 and 7 DF, p-value: 0.7151Varari_avgSGD_NEC2 <- lm(avg_umol ~ poly(SGD_number, degree=2), data = NEC_wnuts_averaged_V)
summary(Varari_avgSGD_NEC2)##
## Call:
## lm(formula = avg_umol ~ poly(SGD_number, degree = 2), data = NEC_wnuts_averaged_V)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.088053 -0.004235 0.011950 0.017120 0.069982
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.37852 0.01883 20.100 9.85e-07 ***
## poly(SGD_number, degree = 2)1 -0.01995 0.05650 -0.353 0.736
## poly(SGD_number, degree = 2)2 0.01129 0.05650 0.200 0.848
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0565 on 6 degrees of freedom
## Multiple R-squared: 0.02671, Adjusted R-squared: -0.2977
## F-statistic: 0.08233 on 2 and 6 DF, p-value: 0.922## cabral
Cabral_avgSGD_NEC <- lm(avg_umol ~ SGD_number, data = NEC_wnuts_averaged_C)
summary(Cabral_avgSGD_NEC)##
## Call:
## lm(formula = avg_umol ~ SGD_number, data = NEC_wnuts_averaged_C)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.05790 -0.01785 0.01022 0.01606 0.04641
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.41538 0.01546 26.867 2.54e-08 ***
## SGD_number -0.01231 0.01006 -1.223 0.261
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03856 on 7 degrees of freedom
## Multiple R-squared: 0.1761, Adjusted R-squared: 0.05845
## F-statistic: 1.497 on 1 and 7 DF, p-value: 0.2608Creating plots for N:P (x axis) and Rates on y axis
- taking ratio of Nitrates to Phosphates at each dilution and then use that against R/GP/NP/NEC
## First make all new dfs
FULL_RespoNEC_allParams2 <- RespoR_Normalized_Full_AllInfo %>%
group_by(P_R, SGD_number, date, site, new_colonynumber) %>%
mutate(N_P = NN_umolL/phosphate_umolL,
P_N = phosphate_umolL/NN_umolL)
## Varari GP
Nutrient_Models_Varari_GP2 <- FULL_RespoNEC_allParams2 %>%
filter(site=="Varari") %>%
drop_na(NN_umolL) %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr))
### Varari NP
Nutrient_Models_Varari_NP2 <- FULL_RespoNEC_allParams2 %>%
filter(site=="Varari") %>%
drop_na(NN_umolL) %>%
filter(P_R=="NP") %>%
filter(!is.infinite(umol.cm2.hr))
### Varari R
Nutrient_Models_Varari_R2 <- FULL_RespoNEC_allParams2 %>%
filter(site=="Varari") %>%
drop_na(NN_umolL) %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr))
### Varari C
Nutrient_Models_Varari_C2 <- FULL_RespoNEC_allParams2 %>%
filter(site=="Varari") %>%
drop_na(NN_umolL) %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr))
### Cabral GP
Nutrient_Models_Cabral_GP2 <- FULL_RespoNEC_allParams2 %>%
filter(site=="Cabral") %>%
drop_na(NN_umolL) %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr))
### Cabral NP
Nutrient_Models_Cabral_NP2 <- FULL_RespoNEC_allParams2 %>%
filter(site=="Cabral") %>%
drop_na(NN_umolL) %>%
filter(P_R=="NP") %>%
filter(!is.infinite(umol.cm2.hr))
### Cabral R
Nutrient_Models_Cabral_R2 <- FULL_RespoNEC_allParams2 %>%
filter(site=="Cabral") %>%
drop_na(NN_umolL) %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr))
### Cabral C
Nutrient_Models_Cabral_C2 <- FULL_RespoNEC_allParams2 %>%
filter(site=="Cabral") %>%
drop_na(NN_umolL) %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr))Now make plots
#################################
### VARARI FIRST
#################################
##############
## GP
##############
N_PRatiobyGPplot_V <- Nutrient_Models_Varari_GP2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(N_P+1),
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method = "lm") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged N:P Ratio",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with N:P Ratio") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
N_PRatiobyGPplot_V
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "N_P_Ratios", "GP_plot.jpg"),
width = 10, height = 7)
##############
## NP
##############
N_PRatiobyNPplot_V <- Nutrient_Models_Varari_NP2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=N_P,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
geom_smooth(method="lm") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged N:P Ratio",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Varari with N:P Ratio") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
N_PRatiobyNPplot_V
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "N_P_Ratios", "NP_plot.jpg"),
width = 10, height = 7)
##############
## R
##############
N_PRatiobyRplot_V <- Nutrient_Models_Varari_R2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(N_P+1),
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method="lm") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged N:P Ratio",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Varari with N:P Ratio") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
N_PRatiobyRplot_V
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "N_P_Ratios", "R_plot.jpg"),
width = 10, height = 7)
#########################################
## model to check if sig
#########################################
model_V_NPratiobyR <- lmer(umol.cm2.hr ~ log(N_P+1) + (1|new_colonynumber) , data=Nutrient_Models_Varari_R2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)))
anova(model_V_NPratiobyR)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(N_P + 1) 0.0017878 0.0017878 1 66.941 0.5688 0.4534##############
## NEC
##############
N_PRatiobyNECplot_V <- Nutrient_Models_Varari_C2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(N_P+1),
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method="lm") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged N:P Ratio",
y = "Rate (umol O2 cm2 hr-1)",
title = "NEC Rates for Varari with N:P Ratio") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
N_PRatiobyNECplot_V
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "N_P_Ratios", "NEC_plot.jpg"),
width = 10, height = 7)
#######################################
## now Cabral plots
#######################################
##################
## GP
##################
N_PRatiobyGPplot_C <- Nutrient_Models_Cabral_GP2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(N_P+1),
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method = "lm") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged N:P Ratio",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with N:P Ratio") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
N_PRatiobyGPplot_C
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "N_P_Ratios", "GP_plot.jpg"),
width = 10, height = 7)
#########################################
## model to check if sig - it is not
#########################################
model_C_NPratiobyGP <- lmer(umol.cm2.hr ~ log(N_P+1) + (1|new_colonynumber) ,data=Nutrient_Models_Cabral_GP2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)))
anova(model_C_NPratiobyGP)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(N_P + 1) 0.013621 0.013621 1 51 0.9165 0.3429##################
## NP
##################
N_PRatiobyNPplot_C <- Nutrient_Models_Cabral_NP2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(N_P+1),
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method="lm") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged N:P Ratio",
y = "Rate (umol O2 cm2 hr-1)",
title = "NP Rates for Cabral with N:P Ratio") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
N_PRatiobyNPplot_C
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "N_P_Ratios", "NP_plot.jpg"),
width = 10, height = 7)
##################
## R
##################
N_PRatiobyRplot_C <- Nutrient_Models_Cabral_R2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(N_P+1),
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method="lm") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged N:P Ratio",
y = "Rate (umol O2 cm2 hr-1)",
title = "R Rates for Cabral with N:P Ratio") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
N_PRatiobyRplot_C
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "N_P_Ratios", "R_plot.jpg"),
width = 10, height = 7)
#########################################
## model to check if sig
#########################################
model_C_NPratiobyNEC <- lmer(umol.cm2.hr ~ log(N_P+1) + (1|new_colonynumber) ,data=Nutrient_Models_Cabral_R2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)))
anova(model_C_NPratiobyNEC)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(N_P + 1) 0.014084 0.014084 1 49.56 3.9089 0.05361 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##################
## NEC
##################
N_PRatiobyNECplot_C <- Nutrient_Models_Cabral_C2 %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(N_P+1),
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method="lm") +
# facet_wrap(~date, scales = "free_x") +
labs(x = "Logged N:P Ratio",
y = "Rate (umol O2 cm2 hr-1)",
title = "NEC Rates for Cabral with N:P Ratio") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
N_PRatiobyNECplot_C
ggsave(here("Outputs", "NutrientAnalyses", "Cabral", "N_P_Ratios", "NEC_plot.jpg"),
width = 10, height = 7)Creating plots for GP:C at both sites
- Gross Photosynthesis has been shown to impact rates of calcification (include literature here) So look at the rates of GP on x and Calcif. on y to see if there is a relationship here at my sites with my rates
- Findings:
RespoR_Normalized_Full_AllInfo <- RespoR_Normalized_Full_AllInfo %>%
mutate(Salinity=salinity)
FULL_RespoNEC_allParams_GP_C_edit <- RespoR_Normalized_Full_AllInfo %>%
select(!c("phosphate_umolL":"Salinity")) %>%
filter(P_R!="R", P_R!="NP") %>%
pivot_wider(names_from = P_R, values_from = umol.cm2.hr)
#######################################
### Varari plot first
#######################################
C_GP_Relationship_Varari <- FULL_RespoNEC_allParams_GP_C_edit %>%
filter(site=="Varari",
GP<1.3) %>% ## deleted one high GP rate of 1.4 to see if it made a difference in the slope
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=GP,
y=C)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
geom_smooth(method="lm") +
labs(x = "Gross Photosynthesis Rates",
y = "Calcification Rates",
title = "GP:C Relationship for Varari") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
C_GP_Relationship_Varari
#######################
## test with model
#######################
model_C_GPRelationship_Varari <- lmer(C ~ GP + (1|new_colonynumber), data = FULL_RespoNEC_allParams_GP_C_edit %>%
filter(site=="Varari") %>%
drop_na(C, GP) %>%
filter(!is.infinite(GP)) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)))
anova(model_C_GPRelationship_Varari)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## GP 0.020595 0.020595 1 66.967 1.2312 0.2711#######################################
### Cabral plot next
#######################################
C_GP_Relationship_Cabral <- FULL_RespoNEC_allParams_GP_C_edit %>%
filter(site=="Cabral") %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=GP,
y=C)) +
geom_point(size=3, aes(color=new_colonynumber)) +
geom_smooth(method="lm") +
theme_bw() +
labs(x = "Gross Photosynthesis Rates",
y = "Calcification Rates",
title = "GP:C Relationship for Cabral") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
C_GP_Relationship_Cabral
#######################
## test with model
#######################
model_C_GPRelationship_Cabral <- lmer(C ~ GP + (1|new_colonynumber), data = FULL_RespoNEC_allParams_GP_C_edit %>%
filter(site=="Cabral") %>%
drop_na(C, GP) %>%
filter(!is.infinite(GP)) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)))
anova(model_C_GPRelationship_Cabral)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## GP 0.01523 0.01523 1 49.271 2.095 0.1541C_GP_Relationship_Cabral + C_GP_Relationship_Varari
ggsave(here("Outputs", "NutrientAnalyses", "Varari", "bothsites_GP_C_Relationship.jpg"),
width = 15, height = 7)Creating plots for GP/R per env parameter
## First make all new dfs
FULL_RespoNEC_allParams_GP_R_EnvParams <- RespoR_Normalized_Full_AllInfo %>%
dplyr::select(!"sample_ID") %>%
group_by(P_R, SGD_number, date, site, new_colonynumber) %>%
filter(P_R!="C", P_R!="NP") %>%
#summarize(GP_R = GP/R)
pivot_wider(names_from = P_R, values_from = umol.cm2.hr) %>%
mutate(GP_R = GP/R)
FULL_RespoNEC_allParams_GP_R_EnvParams_2 <- FULL_RespoNEC_allParams_GP_R_EnvParams %>%
filter(phosphate_umolL<1, salinity >30) %>%
pivot_longer(cols = phosphate_umolL:Salinity, names_to = "EnvParams", values_to="EnvMeasurements")
#### IF decide to go with this, not perfect, still
###############################################
### make plots, facet by env parameter
###############################################
#### Varari plots first
R_GP_byEnvParams_Varari <- FULL_RespoNEC_allParams_GP_R_EnvParams_2 %>%
filter(site=="Varari") %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(EnvMeasurements+1),
y=GP_R)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
facet_wrap(~EnvParams, scales = "free_x") +
geom_smooth(method="lm") +
labs(x = "Environmental Parameters",
y = "Gross Photosynthesis/Respiration Rates",
title = "Env Params by GP:R Relationship for Varari") +
theme(axis.text.x=element_text(size=12),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
R_GP_byEnvParams_Varari
#model_R_GPRelationship_Varari <- lmer(R ~ GP + (1|new_colonynumber), data = FULL_RespoNEC_allParams_GP_R_EnvParams_2 %>%
# filter(site=="Varari"),
# filter(!is.infinite(R)),
#drop_na())
#### Cabral plots first
R_GP_byEnvParams_Cabral <- FULL_RespoNEC_allParams_GP_R_EnvParams_2 %>%
filter(site=="Cabral") %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(EnvMeasurements+1),
y=GP_R)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
facet_wrap(~EnvParams, scales = "free_x") +
geom_smooth(method="lm") +
labs(x = "Environmental Parameters",
y = "Gross Photosynthesis/Respiration Rates",
title = "Env Params by GP:R Relationship for Cabral") +
theme(axis.text.x=element_text(size=12),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
R_GP_byEnvParams_Cabral
## doesn't look like much going on for relationships hereTIMELINE UPDATES
June 11th updates from Nyssa
Look to see if TA and Salinity are correlated
### Varari TA and Salinity relationship
TAbySalinityplot_V <- RespoR_Normalized_Full_AllInfo %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=TA_initial,
y=Salinity)) +
geom_point(aes(color=new_colonynumber), size=3) +
theme_bw() +
coord_trans(x="log") +
#geom_smooth(method="lm") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
#facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "TA",
y = "Salinty",
title = "Salinity vs TA Correlation for Varari (Logged Values)") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
TAbySalinityplot_V
modelTA_Salinity_V <- lmer(Salinity ~ TA_initial + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo)
anova(modelTA_Salinity_V)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## TA_initial 40.518 40.518 1 491.1 364.81 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Make geom_smooth lines based on models specifically - only with the top, significant models
##############
## quick model
###############
modelPhos_NEC_V <- lmer(umol.cm2.hr ~ poly(phosphate_umolL, degree=2) + (1|new_colonynumber), data=Nutrient_Models_Varari_NEC)
anova(modelPhos_NEC_V)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value
## poly(phosphate_umolL, degree = 2) 0.24722 0.12361 2 61.029 9.3418
## Pr(>F)
## poly(phosphate_umolL, degree = 2) 0.0002888 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1### Phos
PhosbyVplot <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
filter(phosphate_umolL<0.7) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=phosphate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
theme_bw() +
geom_smooth(method="lmer", formula="umol.cm2.hr ~ poly(phosphate_umolL, degree=2) + (1|new_colonynumber)") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "Phosphate",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with Phosphate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
PhosbyVplot
ggsave(here::here("Outputs", "NutrientAnalyses", "Varari", "Calcification", "NECbyPhosphate.jpg"))plotting salinity on the x and NEC on the y
NEC_Salinity_V <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=salinity,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
#geom_smooth(method="lmer", formula="umol.cm2.hr ~ poly(phosphate_umolL, degree=2) + (1|new_colonynumber)") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "Salinity",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with Salinity") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NEC_Salinity_V
NEC_TA_V <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date),
SGD_number=as.factor(SGD_number)) %>%
ggplot(aes(x=TA_initial,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#geom_smooth(method="lmer", formula="umol.cm2.hr ~ poly(phosphate_umolL, degree=2) + (1|new_colonynumber)") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "TA",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with TA") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NEC_TA_V
NEC_Silicate_V <- Nutrient_Models_Varari_NEC %>%
drop_na(umol.cm2.hr) %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date),
SGD_number=as.factor(SGD_number)) %>%
ggplot(aes(x=silicate_umolL,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
coord_trans(x="log") +
#geom_smooth(method="lmer", formula="umol.cm2.hr ~ poly(phosphate_umolL, degree=2) + (1|new_colonynumber)") +
#scale_color_manual(values=pnw_palette("Sailboat")) +
# facet_wrap(~new_colonynumber, scales = "free_x") +
labs(x = "Silicate",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with Silicate") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
NEC_Silicate_V
NEC_TA_V + NEC_Silicate_V
RESULTS SECTION as of June 13th
Currently: not really seeing results that make sense with isolating each nutrient/env parameter on the x-axis. Think about this more, but right now, keep SGD on the x-axis
- Only include SGD dils as the x-axis and then GP, R, and C
Respiration
Results: No significant linear relationship of SGD level on either Cabral (0.99) or Varari (0.14) OR nonlinear
###########################
### For Varari
###########################
SGDdilsbyV_Resp <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=4, aes(color=new_colonynumber)) +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
coord_trans(x ="log") +
theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method = "lm", color="black") +
geom_hline(yintercept = 0) +
labs(x = "log SGD Dils",
y = "Rate (umol O2 cm2 hr-1)",
title = "Resp Rates for Varari with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyV_Resp
### testing in a model
model_ex_RespoV <- lmer(umol.cm2.hr ~ log(SGD_number+1) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex_RespoV)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(SGD_number + 1) 0.0066251 0.0066251 1 59.962 2.1962 0.1436### testing in a nonlinear model
model_ex_RespoV_nonlin <- lmer(umol.cm2.hr ~ poly(log(SGD_number+1),2) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex_RespoV_nonlin)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(log(SGD_number + 1), 2) 0.012828 0.0064138 2 58.984 2.1691 0.1233###################
## for Cabral
####################
SGDdilsbyC_Resp <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=4, aes(color=new_colonynumber)) +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
coord_trans(x ="log") +
theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method = "lm", color="black") +
geom_hline(yintercept = 0) +
labs(x = "log SGD Dils",
y = "Rate (umol O2 cm2 hr-1)",
title = "Respo Rates for Cabral with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyC_Resp
### testing in a model
model_ex_RespoC <- lmer(umol.cm2.hr ~ log(SGD_number+1) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex_RespoC)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(SGD_number + 1) 9.037e-08 9.037e-08 1 46.085 0 0.9962### testing in a nonlinear model
model_ex_RespoC_nonlin <- lmer(umol.cm2.hr ~ poly(log(SGD_number+1),2) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="R") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex_RespoC_nonlin)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(log(SGD_number + 1), 2) 0.011554 0.0057771 2 45.076 1.5607 0.2211Gross Photosynthesis
Results: No significant linear relationship of SGD dils on GP rates for Varari (0.4) or Cabral, though Cabral is close at 0.077. - BUT, at Cabral, there is a nonlinear relationship to SGD dils (0.02) for GP
###########################
### For Varari
###########################
SGDdilsbyV_GP2 <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=4, aes(color=new_colonynumber)) +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
coord_trans(x ="log") +
theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method="lm", formula = "y~poly(log(x),2)", color="black") +
geom_hline(yintercept = 0) +
labs(x = "log SGD Dils",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Varari with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyV_GP2
### testing in a linear model
model_ex_GP_V <- lmer(umol.cm2.hr ~ log(SGD_number+1) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex_GP_V)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(SGD_number + 1) 0.010297 0.010297 1 60.065 0.4631 0.4988### testing in a nonlinear model
model_ex_GP_V_nonlin <- lmer(umol.cm2.hr ~ poly(log(SGD_number+1),2) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex_GP_V_nonlin)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(log(SGD_number + 1), 2) 0.089681 0.044841 2 59.102 2.1119 0.13###################
## for Cabral
####################
SGDdilsbyC_GP2 <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=4, aes(color=new_colonynumber)) +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
coord_trans(x ="log") +
theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method="lm", formula = "y~poly(log(x),2)", color="black") +
# geom_hline(yintercept = 0) +
labs(x = "log SGD Dils",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyC_GP2
### testing in a linear model
model_ex_C_GP <- lmer(umol.cm2.hr ~ log(SGD_number+1) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex_C_GP)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(SGD_number + 1) 0.045966 0.045966 1 46.338 3.266 0.07722 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1### testing in a nonlinear model
model_ex_C_GP_nonlin <- lmer(umol.cm2.hr ~ poly(log(SGD_number+1),2) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="GP") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex_C_GP_nonlin)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(log(SGD_number + 1), 2) 0.10382 0.051908 2 45.272 3.9695 0.0258 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Calcification
Results: there is a significant linear relationship of SGD (0.008) on calcification rates at Varari (though average remains net calcifying). However, there is no significant relationship of SGD level on calcification at Cabral (0.15) - there is also a nonlinear relationship with C at Varari - though, still nothing at Cabral - phopshate at Varari is significant
###################
## for Varari
####################
SGDdilsbyVplot2 <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=4, aes(color=new_colonynumber)) +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
coord_trans(x ="log") +
theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method = "lm", color="black") +
geom_hline(yintercept = 0) +
labs(x = "log SGD Dils",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Varari with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyVplot2
### testing in a model
model_ex <- lmer(umol.cm2.hr ~ log(SGD_number+1) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(SGD_number + 1) 0.11101 0.11101 1 60.079 7.3097 0.008907 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1### testing in a nonlinear model
model_exC_nonlin_V <- lmer(umol.cm2.hr ~ poly(log(SGD_number+1),2) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Varari") %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_exC_nonlin_V)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(log(SGD_number + 1), 2) 0.12033 0.060163 2 59.118 3.9338 0.02489 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1###################
## for Cabral
####################
SGDdilsbyCplot2 <- RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr)) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=4, aes(color=new_colonynumber)) +
scale_color_manual(values=rev(pnw_palette("Bay", n=9)),
guide="none") +
theme_bw() +
coord_trans(x ="log") +
theme(strip.background = element_rect(fill = "white")) +
geom_smooth(method = "lm", color="black") +
geom_hline(yintercept = 0) +
labs(x = "log SGD Dils",
y = "Rate (umol CaCO3 g-1 hr-1)",
title = "NEC Rates for Cabral with SGD Dils") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDdilsbyCplot2
### testing in a model
model_ex2 <- lmer(umol.cm2.hr ~ log(SGD_number+1) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_ex2)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## log(SGD_number + 1) 0.015433 0.015433 1 46.137 2.1383 0.1504### testing in a nonlinear model
model_exC_nonlin_C <- lmer(umol.cm2.hr ~ poly(log(SGD_number+1),2) + (1|new_colonynumber), data=RespoR_Normalized_Full_AllInfo %>%
filter(site=="Cabral") %>%
filter(P_R=="C") %>%
filter(!is.infinite(umol.cm2.hr)))
anova(model_exC_nonlin_C)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(log(SGD_number + 1), 2) 0.01618 0.0080902 2 45.126 1.0993 0.3418Plot GP:R Ratio as a function of SGD
Not completed yet
## First make all new dfs
FULL_RespoNEC_allParams_GP_R_EnvParams <- RespoR_Normalized_Full_AllInfo %>%
dplyr::select(!"sample_ID") %>%
group_by(P_R, SGD_number, date, site, new_colonynumber) %>%
filter(P_R!="C", P_R!="NP") %>%
#summarize(GP_R = GP/R)
pivot_wider(names_from = P_R, values_from = umol.cm2.hr) %>%
mutate(GP_R = GP/R)
FULL_RespoNEC_allParams_GP_R_EnvParams_2 <- FULL_RespoNEC_allParams_GP_R_EnvParams %>%
filter(phosphate_umolL<1, salinity >30) %>%
pivot_longer(cols = phosphate_umolL:Salinity, names_to = "EnvParams", values_to="EnvMeasurements")
###############################################
### make plots, facet by env parameter
###############################################
#### Varari plots first
R_GP_byEnvParams_Varari <- FULL_RespoNEC_allParams_GP_R_EnvParams_2 %>%
filter(site=="Varari") %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
ggplot(aes(x=log(EnvMeasurements+1),
y=GP_R)) +
geom_point(size=3, aes(color=new_colonynumber)) +
theme_bw() +
facet_wrap(~EnvParams, scales = "free_x") +
geom_smooth(method="lm") +
labs(x = "Environmental Parameters",
y = "Gross Photosynthesis/Respiration Rates",
title = "Env Params by GP:R Relationship for Varari") +
theme(axis.text.x=element_text(size=12),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
R_GP_byEnvParams_Varari
model_C_GPRelationship_Varari <- lmer(R ~ GP + (1|new_colonynumber), data = FULL_RespoNEC_allParams_GP_R_EnvParams_2 %>%
filter(site=="Varari") %>%
drop_na(EnvMeasurements) %>%
filter(!is.infinite(R)))
#############################
###### WITH NYSSA
#############################
modelex2 <- lmer(umol.cm2.hr ~ poly(log(SGD_number+1),2) + (1|new_colonynumber), Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber)) %>%
filter(!is.infinite(umol.cm2.hr)))
anova(modelex2)## Type III Analysis of Variance Table with Satterthwaite's method
## Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
## poly(log(SGD_number + 1), 2) 0.10382 0.051908 2 45.272 3.9695 0.0258 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## SGD
SGDbyGPplot <- Nutrient_Models_Cabral_GP %>%
mutate(new_colonynumber= as.factor(new_colonynumber),
date=as.factor(date)) %>%
ggplot(aes(x=SGD_number+1,
y=umol.cm2.hr)) +
geom_point(size=3, aes(color=new_colonynumber)) +
coord_trans(x="log") +
geom_smooth(method="lm", formula = "y~poly(log(x),2)") +
theme_bw() +
# facet_wrap(~date, scales = "free_x") +
labs(x = "SGD",
y = "Rate (umol O2 cm2 hr-1)",
title = "GP Rates for Cabral with SGD") +
theme(axis.text.x=element_text(size=18),
axis.text.y=element_text(size=18),
axis.title.x=element_text(size=18),
axis.title.y=element_text(size=18),
plot.title=element_text(hjust=0.5, ## centers title
size=20))
SGDbyGPplot